Key Responsibilities
Machine Learning & Analytics Delivery
Develop, implement, and operationalize advanced data and analytics models to guide retail decision-making (e.g., performance analysis, customer segmentation, demand forecasting, impact measurement, ranking/recommendation systems).
Lead the full lifecycle of solution delivery: from problem definition → data scoping → model development → validation → deployment → monitoring → continuous improvement, with clear success metrics and adoption targets.
Ensure models remain robust, scalable, and reliable in production by monitoring data quality, detecting drift, and managing retraining schedules.

Generative AI Expertise & Application
Possess strong knowledge of GenAI/LLM principles, limitations, and risks (prompt engineering, context boundaries, hallucination issues, retrieval/RAG strategies, evaluation frameworks, and guardrails).
Partner with LLM engineers to integrate GenAI into category management workflows (e.g., automated insight summaries, natural language to SQL, agent-driven analytics, RAG applied to category documentation), ensuring measurable improvements and governance.

Business Collaboration & Delivery Excellence
Engage closely with business stakeholders to clarify requirements, validate assumptions, and ensure outputs align with real-world decision processes.
Communicate trade-offs effectively (speed vs. accuracy, complexity vs. maintainability) and proactively manage scope, risks, and expectations.
Mentor junior colleagues, instill best practices, and elevate delivery standards across documentation, testing, and experimentation.

Qualifications & Requirements
Bachelor’s or Master’s degree in Computer Science, Mathematics, Data Science, or related disciplines.
Minimum 5 years of experience in data science/applied machine learning, with proven track record of delivering end-to-end ML/analytics solutions in production settings.
Hands-on experience with GenAI/LLM systems (RAG, evaluation, guardrails) and ability to articulate system behaviors clearly.
Strong programming skills in Python, with advanced SQL and data manipulation expertise.
Experience in deploying, optimizing, and monitoring models (CI/CD pipelines, version control, performance tracking, incident resolution).
Demonstrated ability to manage stakeholders, drive clarity in ambiguous projects, and deliver outcomes independently.
Excellent communication and teamwork skills.
Prior exposure to retail/FMCG domains (customer behavior, assortment, pricing, promotions) is a plus.
Proficiency in both spoken and written English and Chinese.

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